Data practitioners
You can say what the number means. Nothing downstream can.
Semcore holds the definitions your business runs on above the warehouse and beneath everything that queries it, so the meaning you agreed is the meaning every report, model and assistant reads.
You are the place the disagreement lands
The definition of an active customer sits in a query somebody wrote, a transformation model somebody else owns, a spreadsheet finance keeps and the head of whoever was there first. Each version was reasonable where it was written. None of them was written anywhere the others could see it.
So the work is not modelling. It is reconstruction: opening four definitions, working out which one the figure in front of you came from, and explaining the difference to somebody who only wanted the number.
And nothing announces a change. A definition is edited, nothing downstream refuses to build, and the first person to find out is whoever is asked why the board pack and the report disagree.
What you can do
Three of the entries in the catalog are written for this work, and each one takes a piece of it off your desk.
Start from a draft rather than a blank file
Domains, models and definitions are drafted across your catalog and handed to you to review, which is the half of modelling that consumes analyst quarters.
Put a change in front of somebody before it lands
A change to what a term means goes to a reviewer the way a change to code does, and what it meant before is recorded rather than reconstructed later.
Keep dbt and the semantic layer in step
The semantic models and metrics your dbt project already defines are held to the same governance as the rest of the estate, instead of drifting away from it.
The catalog entries behind this, and what each one lets you do.
- 01Agentic Modelling CopilotDomains, models and definitions drafted across your catalog, rather than assembled by hand.Modelling that consumes analyst quarters arrives as a draft to review.
- 03Model Change ReviewEvery change to a data model put in front of a reviewer before it lands, the way code already is.A change to what a number means is approved and recorded, and nobody learns about it from a figure that moved.
- 04Governed MetricsThe semantic models and metrics your dbt project already defines, held to the same governance as the rest of the estate.Your transformation layer and your semantic layer stay in step instead of drifting apart.
An AI Readiness Review
A scoping conversation, and a look at your data estate as it stands: what your AI plans will need from it, where the gaps are, and which of them to close first. The findings are yours either way.